{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:J4KP3XF6SGSCFHLH2OWDADX3WM","short_pith_number":"pith:J4KP3XF6","schema_version":"1.0","canonical_sha256":"4f14fddcbe91a4229d67d3ac300efbb305c0eff6d745c710dc3349dce9ad56b9","source":{"kind":"arxiv","id":"2308.10944","version":3},"attestation_state":"computed","paper":{"title":"Towards an astronomical foundation model for stars with a Transformer-based model","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.GA","astro-ph.SR"],"primary_cat":"astro-ph.IM","authors_text":"Henry W. Leung, Jo Bovy","submitted_at":"2023-08-21T18:00:05Z","abstract_excerpt":"Rapid strides are currently being made in the field of artificial intelligence using Transformer-based models like Large Language Models (LLMs). The potential of these methods for creating a single, large, versatile model in astronomy has not yet been explored. In this work, we propose a framework for data-driven astronomy that uses the same core techniques and architecture as used by LLMs. Using a variety of observations and labels of stars as an example, we build a Transformer-based model and train it in a self-supervised manner with cross-survey data sets to perform a variety of inference t"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2308.10944","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.IM","submitted_at":"2023-08-21T18:00:05Z","cross_cats_sorted":["astro-ph.GA","astro-ph.SR"],"title_canon_sha256":"4a495f403df8420abb0b4d1bb8dade318382d94bdd481b491664c14fef5f3c46","abstract_canon_sha256":"15097be2aa5cb0384760469c1e079d3930232a0616d1deaee0a38441b2cdc7bd"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:08:29.205381Z","signature_b64":"/3I+9wFwwJUpqU+WjCFZ+McZzVgoNGe5aUuk7SSWanCtswTvQB3HY8tESecUCzsnrssLgVFAM1fzrpN94DmLBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4f14fddcbe91a4229d67d3ac300efbb305c0eff6d745c710dc3349dce9ad56b9","last_reissued_at":"2026-07-05T07:08:29.204973Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:08:29.204973Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Towards an astronomical foundation model for stars with a Transformer-based model","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.GA","astro-ph.SR"],"primary_cat":"astro-ph.IM","authors_text":"Henry W. Leung, Jo Bovy","submitted_at":"2023-08-21T18:00:05Z","abstract_excerpt":"Rapid strides are currently being made in the field of artificial intelligence using Transformer-based models like Large Language Models (LLMs). The potential of these methods for creating a single, large, versatile model in astronomy has not yet been explored. In this work, we propose a framework for data-driven astronomy that uses the same core techniques and architecture as used by LLMs. Using a variety of observations and labels of stars as an example, we build a Transformer-based model and train it in a self-supervised manner with cross-survey data sets to perform a variety of inference t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.10944","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2308.10944/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2308.10944","created_at":"2026-07-05T07:08:29.205030+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.10944v3","created_at":"2026-07-05T07:08:29.205030+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.10944","created_at":"2026-07-05T07:08:29.205030+00:00"},{"alias_kind":"pith_short_12","alias_value":"J4KP3XF6SGSC","created_at":"2026-07-05T07:08:29.205030+00:00"},{"alias_kind":"pith_short_16","alias_value":"J4KP3XF6SGSCFHLH","created_at":"2026-07-05T07:08:29.205030+00:00"},{"alias_kind":"pith_short_8","alias_value":"J4KP3XF6","created_at":"2026-07-05T07:08:29.205030+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/J4KP3XF6SGSCFHLH2OWDADX3WM","json":"https://pith.science/pith/J4KP3XF6SGSCFHLH2OWDADX3WM.json","graph_json":"https://pith.science/api/pith-number/J4KP3XF6SGSCFHLH2OWDADX3WM/graph.json","events_json":"https://pith.science/api/pith-number/J4KP3XF6SGSCFHLH2OWDADX3WM/events.json","paper":"https://pith.science/paper/J4KP3XF6"},"agent_actions":{"view_html":"https://pith.science/pith/J4KP3XF6SGSCFHLH2OWDADX3WM","download_json":"https://pith.science/pith/J4KP3XF6SGSCFHLH2OWDADX3WM.json","view_paper":"https://pith.science/paper/J4KP3XF6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.10944&json=true","fetch_graph":"https://pith.science/api/pith-number/J4KP3XF6SGSCFHLH2OWDADX3WM/graph.json","fetch_events":"https://pith.science/api/pith-number/J4KP3XF6SGSCFHLH2OWDADX3WM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/J4KP3XF6SGSCFHLH2OWDADX3WM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/J4KP3XF6SGSCFHLH2OWDADX3WM/action/storage_attestation","attest_author":"https://pith.science/pith/J4KP3XF6SGSCFHLH2OWDADX3WM/action/author_attestation","sign_citation":"https://pith.science/pith/J4KP3XF6SGSCFHLH2OWDADX3WM/action/citation_signature","submit_replication":"https://pith.science/pith/J4KP3XF6SGSCFHLH2OWDADX3WM/action/replication_record"}},"created_at":"2026-07-05T07:08:29.205030+00:00","updated_at":"2026-07-05T07:08:29.205030+00:00"}